The present study was conducted to establish prediction models for grain yield and nitrogen (N) uptake using normalized difference vegetation index (NDVI) measurements with the GreenSeeker optical sensor for different cultivar groups of basmati rice (Oryza sativa L.) and to define the optimum sensing timing. Sensor readings were collected at 21, 28, 35, 42, and 49 days after transplanting (DAT) from multi-cultivar and multi-rate N fertilization experiments conducted in 2016 and 2017. Prediction model established by regressing NDVI day⁻¹ as the determinant of plant biomass with grain yield and N uptake at maturity following exponential functions revealed that sensing the crop before or after 35 DAT (panicle initiation stage) was not accurate and did not predict satisfactorily the yield or N uptake potential. Regression analysis generated two potential and viable yield or N uptake prediction models: one for the basmati rice cultivar CSR30 (tall cultivar), and the other for a PB-PUSA (group of semi-dwarf cultivars). Validation of the prediction models using an independent experiment conducted in 2018 revealed that sensing the crop at the panicle initiation stage provide grain yield and N uptake predictions close to the observed grain yield (R² = 0.86, RMSE = 6.1%) and N uptake (R² = 0.75, RMSE = 8.5%). This study showed that yield and N uptake potential in basmati rice can be predicted using in-season NDVI data measured with the GreenSeeker optical sensor.

本研究旨在建立使用归一化差异植被指数 (NDVI) 测量值和 GreenSeeker 光学传感器对不同栽培品种印度香稻 ( Oryza sativa L.) 的谷物产量和氮 (N) 吸收的预测模型，并确定最佳模型。感测时机。从2016年和2017年进行的多品种和多比率施氮试验中，在移栽后21、28、35、42和49天（DAT）收集传感器读数。 通过回归NDVI第^-1天建立预测模型作为植物生物量与谷物产量和成熟时 N 吸收的指数函数的决定因素表明，在 35 DAT（穗起始阶段）之前或之后感知作物是不准确的，并且不能令人满意地预测产量或 N 吸收潜力。回归分析产生了两种潜在和可行的产量或氮吸收预测模型：一种用于巴斯马蒂水稻品种 CSR30（高大品种），另一种用于 PB-PUSA（半矮化品种组）。使用 2018 年进行的独立实验验证预测模型表明，在穗开始阶段感知作物提供的谷物产量和 N 吸收预测接近于观察到的谷物产量（R ²  = 0.86，RMSE = 6.1%）和 N 吸收（ [R ² = 0.75，RMSE = 8.5%）。该研究表明，可以使用 GreenSeeker 光学传感器测量的当季 NDVI 数据预测印度香米的产量和氮吸收潜力。